Active Learning of Mealy Machines with Timers
Véronique Bruyère, Bharat Garhewal, Guillermo A. Pérez, Gaëtan Staquet, Frits Vaandrager · arXiv (Cornell University) · 2024
We present the first algorithm for query learning Mealy machines with timers in a black-box context. Our algorithm is an extension of the L# algorithm of Vaandrager et al. to a timed setting. We rely on symbolic queries which empower us to reason on untimed executions while learning. Similarly to the algorithm for learning timed automata of Waga, these symbolic queries can be realized using finitely many concrete queries. Experiments with a prototype implementation show that our algorithm is able to efficiently learn realistic benchmarks.